Gray Box Identification Using Difference of Convex Programming
نویسندگان
چکیده
منابع مشابه
Gray Box Identification of State-Space Models Using Difference of Convex Programming
Gray-box identification is prevalent in modeling physical and networked systems. However, due to the nonconvex nature of the gray-box identification problem, good initial parameter estimates are crucial for a successful application. In this paper, a new identification method is proposed by exploiting the low-rank and structured Hankel matrix of impulse response. This identification problem is r...
متن کاملGenetic network identification using convex programming.
Gene regulatory networks capture interactions between genes and other cell substances, resulting in various models for the fundamental biological process of transcription and translation. The expression levels of the genes are typically measured as mRNA concentration in micro-array experiments. In a so-called genetic perturbation experiment, small perturbations are applied to equilibrium states...
متن کاملautomatic verification of authentication protocols using genetic programming
implicit and unobserved errors and vulnerabilities issues usually arise in cryptographic protocols and especially in authentication protocols. this may enable an attacker to make serious damages to the desired system, such as having the access to or changing secret documents, interfering in bank transactions, having access to users’ accounts, or may be having the control all over the syste...
15 صفحه اولGray Box Identification with Hopfield Neural Networks
In this work, a novel method, based upon Hopfield neural networks, is proposed for parameter estimation in the context of system identification. This subject is a very active field of research, because even when a model of a physical system is available, some parameters may be uncertain or time varying. In our methodology, identification is formulated as an optimization problem, profiting from ...
متن کاملFrequency-Domain Gray-Box Identification of Industrial Robots
This paper considers identification of unknown parameters in elastic dynamic models of industrial robots. Identifying such models is a challenging task since an industrial robot is a multivariable, nonlinear, resonant, and unstable system. Unknown parameters (mainly spring-damper pairs) in a physically parameterized nonlinear dynamic model are identified in the frequency domain, using estimates...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IFAC-PapersOnLine
سال: 2017
ISSN: 2405-8963
DOI: 10.1016/j.ifacol.2017.08.1469